Senior Data Scientist

Position Overview: We are seeking a strong Data Scientist to support a strategic data transformation initiative focused on building scalable, AI-enabled data quality and data management capabilities.

The role combines Generative AI, traditional machine learning, and data engineering to develop intelligent solutions for metadata generation, DQ rule recommendation, anomaly detection, entity resolution, profiling automation, and data quality monitoring.

The ideal candidate should be hands-on, technically strong, and able to translate advanced AI/ML methods into practical, production-ready solutions within an enterprise environment.

Key Responsibilities:

• Develop AI-powered solutions using LLMs for metadata enrichment, semantic classification, summarization, and data quality automation
• Build and optimize RAG pipelines grounded in enterprise metadata, profiling outputs, rule libraries, and technical documentation
• Develop ML models for anomaly detection, entity resolution, clustering, predictive analytics, and pattern recognition
• Build scalable Python and SQL pipelines to automate profiling, data onboarding, quality monitoring, and AI-assisted recommendations
• Design Human-in-the-Loop workflows to ensure AI outputs are validated, auditable, and aligned with business requirements
• Collaborate with business, governance, and technical teams to operationalize AI/ML solutions in enterprise environments

Technical Expertise & Skills:

• Strong hands-on experience with LLMs, prompt engineering, and production-grade RAG architectures
• Strong experience in Python, SQL, and ML frameworks such as Scikit-learn, LangChain, LlamaIndex, or equivalent
• Experience with supervised and unsupervised ML techniques, including XGBoost, Random Forest, clustering, PCA, Isolation Forest, and anomaly detection
• Good understanding of metadata management, data quality dimensions, data governance, and enterprise data platforms
• Ability to evaluate model performance, improve output quality, and explain technical results to non-technical stakeholders